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Artificial Neural Network (ANN) for Prediction of Viscosity Reduction of Heavy Crude Oil using Different Organic Solvents
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The increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests  and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a  heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage  (5, 10 and  20 wt.% )  of  (n-heptane, toluene, and a mixture of  different ratio toluene / n-Heptane)  at constant temperature. Experimentally the higher viscosity reduction was about from 135.6 to 26.33 cP when the mixture of toluene/heptane (75/25 vol. %) was added. The input parameters for the model were solvent type, wt. % of solvent, RPM and shear rate, the results have been demonstrated that the proposed model has superior performance, where the obtained value of R was greater than 0.99 which confirms a good agreement between the correlation and experimental data, the predicate for reduced viscosity and DVR was with accuracy 98.7%, on the other hand, the μ and DVR% factors were closer to unity for the ANN model.

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Publication Date
Mon Mar 31 2025
Journal Name
International Journal Of Advanced Technology And Engineering Exploration
Breast cancer survival rate prediction using multimodal deep learning with multigenetic features
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Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

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Publication Date
Sun Jun 30 2024
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Gas Lift Optimization for Zubair Oil Field Using Genetic Algorithm-Based Numerical Simulation: Feasibility Study
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The gas-lift method is crucial for maintaining oil production, particularly from an established field when the natural energy of the reservoirs is depleted. To maximize oil production, a major field's gas injection rate must be distributed as efficiently as possible across its gas-lift network system. Common gas-lift optimization techniques may lose their effectiveness and become unable to replicate the gas-lift optimum in a large network system due to problems with multi-objective, multi-constrained & restricted gas injection rate distribution. The main objective of the research is to determine the possibility of using the genetic algorithm (GA) technique to achieve the optimum distribution for the continuous gas-lift injectio

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Publication Date
Wed Oct 30 2024
Journal Name
Internet Technology Letters
Using <scp>5G</scp> Standards for Smart Healthcare Applications and Designing an Artificial Intelligence‐Based Industry 4.0 Communication System
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ABSTRACT<p>The introduction of Industry 4.0, to improve Internet of Things (IoT) standards, has sparked the creation of 5G, or highly sophisticated wireless networks. There are several barriers standing in the way of 5G green communication systems satisfying the expectations for faster networks, more user capacity, lower resource consumption, and cost‐effectiveness. 5G standards implementation would speed up data transmission and increase the reliability of connected devices for Industry 4.0 applications. The demand for intelligent healthcare systems has increased globally as a result of the introduction of the novel COVID‐19. Designing 5G communication systems presents research problems such as optimizing </p> ... Show More
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Publication Date
Mon Apr 10 2023
Journal Name
The European Physical Journal Plus
Improved performance of D149 dye-sensitized ZnO-based solar cell under solvents activation effect
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Publication Date
Sun Sep 01 2013
Journal Name
Baghdad Science Journal
CMC Determination and Thermodynamic Micellisation Of NPE Surfactant In Aqueous And CH3OH – H2O Solvents
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The critical micelle concentration (CMC) of nonylphenolethoxylate (NPE) surfactant has been determined by measuring the surface tension as a function of the molar concentration of the surfactant in aqueous and binary mixture of water + methanol solutions at a temperature range from 20?C to 35?C. The interfacial parameters ?max, Amin, ?cmc and ?G?ads were calculated. The results indicate that the CMC increases as the temperature increases and that the addition of methanol the CMC decreases. The thermodynamic parameters such as standard Gibbs free energy (?G?), enthalpy (?H?), and entropy (?S?) of micellization were estimated using the change of CMC with temperature. The enthalpy – entropy compensation behavior of the surfactant was evaluat

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Publication Date
Mon Apr 01 2019
Journal Name
International Journal Of Greenhouse Gas Control
CO2-wettability of sandstones exposed to traces of organic acids: Implications for CO2 geo-storage
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Wettability of CO2-brine-mineral systems plays a vital role during geological CO2-storage. Residual trapping is lower in deep saline aquifers where the CO2 is migrating through quartz rich reservoirs but CO2 accumulation within a three-way structural closure would have a high storage volume due to higher CO2 saturation in hydrophobic quartz rich reservoir rock. However, such wettability is only poorly understood at realistic subsurface conditions, which are anoxic or reducing. As a consequence of the reducing environment, the geological formations (i.e. deep saline aquifers) contain appreciable concentrations of various organic acids. We thus demonstrate here what impact traces of organic acids exposed to storage rock have on their wettabil

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Publication Date
Mon Aug 30 2021
Journal Name
Al-kindy College Medical Journal
Diagnostic Evaluation of Uterine Artery Doppler Imaging for the Prediction of Early Abnormal Pregnancy
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Objective: to assess the predictive value of Doppler imaging of the uterine artery in the identification of early intrauterine abnormal pregnancy as compared to a normal intrauterine pregnancy. Subjects and methods: one hundred and twenty pregnant ladies, at their 6-12 weeks of gestation, with a singleton pregnancy were included in this population-based case-control study. Thirty women with a missed miscarriage, 30 with hydatidiform mole, 30 with a blighted ovum, and 30 as a control group, without risk factors, underwent Doppler interrogation of the uterine arteries. Resistive index (RI), pulsatility index (PI), and the systolic/diastolic ratio (S/D) were measured for both sides. The t-test, or ANOVA test when appropriate, was

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Publication Date
Mon Aug 30 2021
Journal Name
Al-kindy College Medical Journal
Diagnostic Evaluation of Uterine Artery Doppler Imaging for the Prediction of Early Abnormal Pregnancy
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Objective: to assess the predictive value of Doppler imaging of the uterine artery in the identification of early intrauterine abnormal pregnancy as compared to a normal intrauterine pregnancy.

Subjects and methods: one hundred and twenty pregnant ladies, at their 6-12 weeks of gestation, with a singleton pregnancy were included in this population-based case-control study. Thirty women with a missed miscarriage, 30 with hydatidiform mole, 30 with a blighted ovum, and 30 as a control group, without risk factors, underwent Doppler interrogation of the uterine arteries. Resistive index (RI), pulsatility index (PI), and the systolic/diastolic ratio (S/D) were measured for both sides. The t-test, or ANOVA test when a

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Publication Date
Fri Jul 01 2016
Journal Name
International Journal Of Advanced Research
Attenuation Coefficient of Reactive Powder Concrete Using Different Energies.
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Linear and mass attenuation coefficient of reactive powder concrete (RPC) sample ( of compressive strength equal to 70 Mpa) using beta particles and gamma ray with different energies have been calculated as a function of the absorber thickness and energy. The attenuation coefficient were obtained using NaI(Tl) energy selective scintillation counter with 90Sr/90Y beta source having an energy rang from (0.546-2.274) MeV and gamma ray energies (0.569, 0.662, 1.063, 1.17 and 1.33) MeV . The attenuation coefficient usually depends upon the energy of radiations and nature of the material. The result represented in graphical forms. Exponential decay was observed. It is found that the capability of reactive powder concrete to absorber beta particle

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Publication Date
Sun Jul 31 2016
Journal Name
International Journal Of Advanced Research
Attenuation Coefficient of Reactive Powder Concrete Using Different Energies.
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